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Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology (USBEREIT)

作者： Mikhail Khachumov Intelligent Control Laboratory Ailamazyan Program Systems Institute of RAS Pereslavl-Zalessky Russia Federal Research Center” Computer Science and Control” of RAS Moscow Russia

The paper gives a statement and considers the solution of an urgent scientific problem of formation control for a group of unmanned aerial vehicles (UAVs) operating in an unstable environment. To construct the reference trajectories and allocate UAVs to positions of a given structure, an original approach is proposed based on the adapted Kohonen neural network with a set of metrics, including Euclidean, Mahalanobis and Euclidean-Mahalanobis distances. To implement the movement of a UAV group in a complex environment, we apply the principles of intelligent-geometric control, which allows to combine flexible intelligent and precise geometric control methods within one concept. When moving along a given route, UAVs use a set of allowable control strategies. The developed modeling scheme is designed to take into account wind loads and possibly dangerous rapprochement of vehicles. To reflect the dynamics of UAVs, a special module is used that contains transfer functions integrated into a single stabilization system with an autopilot. The proposed approach has shown promise when simulating a series of formation control problems.

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Discrete control algorithms for systems with big dead time for control101 MATLAB toolbox

Discrete control algorithms for systems with big dead time f...

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Cybernetics & Informatics (K&I)

作者： Ruth Bars Gyula Max J. Anthony Rossiter László Keviczky Department of Automation and Applied Informatics Budapest University of Technology and Economics Budapest Hungary School of Electrical and Electronic Engineering University of Sheffield Sheffield UK Systems and Control Laboratory Institute for Computer Science and Control Budapest Hungary

ISBN: (数字)9798331541811

ISBN: (纸本)9798331541828

The first course of control is under a critical review. Both the teaching material covered and the teaching methods require new considerations. Introducing interactivity in the education process makes the learning more successful and enjoyable. MATLAB provides an effective environment for learning and applying different disciplines. control101 is a new MATLAB toolbox under development which provides tools for interactive learning of control disciplines. This paper presents the framework for teaching discrete control algorithms applied for processes containing large dead times.

关键词： Visualization Systematics PI control Reviews Education Laboratories Process control Prediction algorithms PD control MATLAB

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State Derivative Normalization for Continuous-Time Deep Neural Networks

arXiv

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arXiv 2024年

作者： Weigand, Jonas Beintema, Gerben I. Ulmen, Jonas Görges, Daniel Tóth, Roland Schoukens, Maarten Ruskowski, Martin Chair of Machine Tools and Control Systems RPTU Kaiserslautern The German Research Center for Artificial Intelligence Kaiserslautern Germany Group The Department of Electrical Engineering Eindhoven University of Technology Netherlands The Systems and Control Laboratory The Institute for Computer Science and Control Budapest Hungary Institute for Electromobility RPTU Kaiserslautern Germany

The importance of proper data normalization for deep neural networks is well known. However, in continuous-time state-space model estimation, it has been observed that improper normalization of either the hidden state or hidden state derivative of the model estimate, or even of the time interval can lead to numerical and optimization challenges with deep learning based methods. This results in a reduced model quality. In this contribution, we show that these three normalization tasks are inherently coupled. Due to the existence of this coupling, we propose a solution to all three normalization challenges by introducing a normalization constant at the state derivative level. We show that the appropriate choice of the normalization constant is related to the dynamics of the to-be-identified system and we derive multiple methods of obtaining an effective normalization constant. We compare and discuss all the normalization strategies on a benchmark problem based on experimental data from a cascaded tanks system and compare our results with other methods of the identification literature. © 2024, CC BY-SA.

关键词： Ordinary differential equations

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All-optical logic gates based on hierarchical photonic crystal modulated photoluminescence of perovskite nanocrystals

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Science China(Technological Sciences) 2023年第9期66卷 2735-2742页

作者： WANG Yun ZHA YanFang YANG YunYi LIU CiHui DI YunSong CAO GuiYuan WEI ShiBiao CHEN ZhiHui GAN ZhiXing Center for Future Optoelectronic Functional Materials School of Computer and Electronic InformationSchool of Artificial IntelligenceNanjing Normal UniversityNanjing 210023China Centre for Translational Atomaterials School of ScienceSwinburne University of TechnologyHawthorn VIC 3122Australia Nanophotonics Research Center Shenzhen Key Laboratory of Micro-Scale Optical Information TechnologyShenzhen UniversityShenzhen 518060China Key Laboratory of Advanced Transducers and Intelligent Control Systems Ministry of Education and Shanxi ProvinceCollege of Electronic Information and Optical EngineeringTaiyuan University of TechnologyTaiyuan 030024China

Halide perovskites exhibit high performance in all sorts of optoelectronic and photonic areas, suggesting their huge potential in integrated photonic devices. However, until now, all optical logic gates based on perovskites are still rarely explored, hindering the development of all-optical networks and computing. Herein, a new concept of all-optical logic gates is proposed based on the modulation of photoluminescence(PL) from perovskite nanocrystals(PNCs). A hierarchical photonic crystal(Hie PhC) is developed by self-assembling polystyrene(PS) and SiO2nanoparticles, which exhibit a higher PL enhancement than that of a monolayer PhC. Moreover, the light-controlled PL is realized by taking advantage of the high thermal response of the PL from PNCs/Hie PhC on polyethylene(PE) substrate, assisted by a graphene layer for light-heat conversion. Consequently, optical diode and triode are achieved based on the modulated PL, which exhibit contrast ratios(CR) of 24.7 and 74.0 dB, ***-optical logic gates, including “AND”, “OR” and “NOT”, are realized based on the optical diode and triode.

关键词： perovskite nanocrystals photonic crystals all-optical logic gates modulation of photoluminescence

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Machine learning insights in predicting heavy metals interaction with biochar

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Biochar 2024年第1期6卷 157-167页

作者： Xin Wei Yang Liu Lin Shen Zhanhui Lu Yuejie Ai Xiangke Wang School of Control and Computer Engineering North China Electric Power UniversityBeijing 102206People’s Republic of China. School of Mathematics and Physics North China Electric Power UniversityBeijing 102206People’s Republic of China. MOE Key Laboratory of Resources and Environmental Systems Optimization College of Environment and Chemical EngineeringNorth China Electric Power UniversityBeijing 102206People’s Republic of China. Key Laboratory of Theoretical and Computational Photochemistry of Ministry of Education College of ChemistryBeijing Normal UniversityBeijing 100875People’s Republic of China.

The use of machine learning(ML)in the field of predicting heavy metals interaction with biochar is a promising field of research,mainly because of the growing understanding of how removal efficiency is affected by characteristic variables,reaction conditions and biochar *** practical application in biochar still faces large challenges,such as difficulties in data collection,inadequate algorithm development,and insufficient ***,the quantity,quality,and representation of data have a large impact on the accuracy,efficiency,and generalizability of machine learning *** this perspective,the present data descriptors,the efficiency of machine learning-aided property and performance prediction,the interpretation of underlying mechanisms and complicated relationships,and some potential ways to augment the data are discussed regarding the interactions of heavy metals with ***,future perspectives and challenges are discussed,and an enhanced model performance is proposed to reinforce the feasibility of a particular perspective.

关键词： Biochar Heavy metals Interaction mechanism Machine learning

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A SINS Error Correction Approach Based on Dual-Threshold ZV Detection and Cubature Kalman Filter

A SINS Error Correction Approach Based on Dual-Threshold ZV ...

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2023 IEEE International Conference on systems, Man, and Cybernetics, SMC 2023

作者： Xu, Ruijie Chen, Shichao Sun, Wenqiao Lv, Yisheng Luo, Jialiang Tang, Ying Institute of Automation Chinese Academy of Sciences College of Information Science & Technology Beijing University of Chemical Technology The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Institute of Automation Chinese Academy of Sciences The Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Corporation Limited The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Transportation and Economics Research Institute The Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Corporation Limited Beijing China Institute of Automation Chinese Academy of Sciences The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Institute of Automation Chinese Academy of Sciences China University of Geosciences Beijing School of Information Engineering The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Rowan University Department of Electrical and Computer Engineering Glassboro United States

ISBN: (纸本)9798350337020

Global Navigation Satellite systems (GNSS) can provide real-time positioning information for outdoor users, but cannot for indoor scenarios or heavily occluded outdoor scenarios. Strap-down Inertial Navigation System (SINS) are widely used to locate people in complex interior or heavily occluded outdoor scenarios due to its light weight and low power consumption. However, IMU of SINS are noisy, and the sampling data error is large, which is a divergence of the error with time. Therefore, it will generate a positioning accumulation error, which affects the final positioning accuracy. The problem of cumulative IMU errors is usually dealt with by Zero-Velocity Update (ZUPT). The zero-velocity detection part of basic ZUPT method usually uses a single threshold to determine the gait of pedestrian, which often has the problem of gait misjudgment and omission. To address these problems, this paper proposes a composite conditional detection method to solve the problem of misjudgment in the zero-velocity interval. In addition, we redesign the zero-velocity update algorithm and uses the Cubature Kalman filter (CKF) for pedestrian positioning error correction. The experimental results demonstrate that the proposed ZUPT method based on dual-threshold detection can better detect the interval between pedestrian motion and stationery than ones with single threshold. The zero-velocity update algorithm based on CKF has higher performance than conventional EKF and UKF methods, which constrains the cumulative error of SINS to about 0.2% of the whole walking distance. © 2023 IEEE.

关键词： Cubature Kalman Filter Inertial Pedestrian Navigation Zero-Velocity Update

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Consensus control of Leader-Following Multi-Agent systems in Directed Topology With Heterogeneous Disturbances

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IEEE/CAA Journal of Automatica Sinica 2021年第2期8卷 423-431页

作者： Qinglai Wei Xin Wang Xiangnan Zhong Naiqi Wu the State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 the School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049and also with Qingdao Academy of Intelligent IndustriesQingdao 266109China the Department of Computer and Electrical Engineering and Computer Science Florida Atlantic UniversityBoca Raton FL33431 USA the Institute of Systems Engineering and Collaborative Laboratory for Intelligent Science and SystemsMacao University of Science and TechnologyMacao 999078China

This paper investigates the consensus problem for linear multi-agent systems with the heterogeneous disturbances generated by the Brown *** main contribution is that a control scheme is designed to achieve the dynamic consensus for the multi-agent systems in directed topology interfered by stochastic *** traditional ways,the coupling weights depending on the communication structure are static.A new distributed controller is designed based on Riccati inequalities,while updating the coupling weights associated with the gain matrix by state errors between adjacent *** introducing time-varying coupling weights into this novel control law,the state errors between leader and followers asymptotically converge to the minimum value utilizing the local *** the Lyapunov directed method and It?formula,the stability of the closed-loop system with the proposed control law is *** simulation results conducted by the new and traditional schemes are presented to demonstrate the effectiveness and advantage of the developed control method.

关键词： Consensus control directed topology external disturbance multi-agent(MA)systems

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Robust control of Feeding Speed in Coal Seam Drilling Process Considering Borehole Friction

Robust Control of Feeding Speed in Coal Seam Drilling Proces...

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2024 China Automation Congress, CAC 2024

作者： Liu, Xiao Chen, Luefeng Lu, Chengda Fan, Haipeng Wu, Min Pedrycz, Witold School of Automation The Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems The Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China University of Geosciences Wuhan430074 China Department of Electrical and Computer Engineering University of Alberta EdmontonABT6G 2R3 Canada Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland Department of Computer Engineering Istinye University Sariyer Istanbul34396 Turkey

ISBN: (纸本)9798350368604

During the coal seam drilling process, the drill string is subject to compressive deformation, compounded by unpredictable variations in formation hardness and borehole wall friction, leading to challenges in maintaining a stable feeding speed. This paper presents a novel approach by introducing uncertain parameters to describe the effects of formation hardness and borehole wall friction. Drill string axial movement model is modeled as a polyhedral system based on a lumped parameter representation. To meet industrial performance requirements, we design a robust H∞ controller to achieve consistent feeding speed control. Our simulation results demonstrate the controller’s effectiveness in ensuring system stability despite fluctuations in formation hardness and drill string friction. © 2024 IEEE.

关键词： Coal deposits

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A Test Suite and An Optimizer for Dietary Nutrition Optimization Problem: From Constrained Many-Objective Perspective

A Test Suite and An Optimizer for Dietary Nutrition Optimiza...

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2023 IEEE Congress on Evolutionary Computation, CEC 2023

作者： Ti, Yaqi Li, Changhe Yang, Shengxiang Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China School of Computer Science and Informatics De Montfort University Leicester United Kingdom

ISBN: (纸本)9798350314588

With increasing people who suffer from diet-related diseases, providing suggestions for personal daily nutrient-dense intake is highly expected. However, current dietary nutrition models are less precise, and dietary nutrition optimizers usually fail to give satisfactory solutions. Therefore, we construct a constrained many-objective nutrition model with more precise nutrient assessments and a scalable constrained many-objective benchmark set. This test suite has great flexibility in evaluating algorithms' performance on high dimensional search and objective spaces with some feasible region fragments. We also propose a kd-tree based dynamic constrained many-objective evolutionary algorithm to search for customized food combinations according to personal daily consumption and intake preference. Experiments show that our algorithm has better diversity maintenance ability in high dimension space. © 2023 IEEE.

关键词： Nutrition

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Application of Extreme Learning Machine for Shunt Faults Detection and Classification in Three-phase Transmission Line systems 3

Application of Extreme Learning Machine for Shunt Faults Det...

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3rd IEEE International Conference on Signal, control and Communication, SCC 2023

作者： Assadi, Khaoula Slimane, Jihane Ben Salhi, Salah University of Tunis El Manar National Engineering School of Tunis LR11ES20 Analysis Design and Control of Systems Laboratory Tunis1002 Tunisia Northern Border University Faculty of Computing and InformationTechnology Department of Computer Sciences Rafha91911 Saudi Arabia

ISBN: (纸本)9798350326390

The electrical power transmission lines play a crucial role in maintaining a continuous electricity supply. However, the exposed environment of these lines increases the risks of faults occurrence, necessitating prompt detection, and classification, to eliminate them within a specified time. In light of this, the present study introduces a methodology for the detection and classification of faults in a three-phase transmission line system employing the Extreme Learning Machine (ELM). A 220 kV, 300 km three-phase transmission line system was simulated in MATLAB/Simulink software, where the current and voltage signals were generated under different fault conditions including fault types, fault inception time, and fault resistance. The fundamental components of these signals were used as inputs in the ELM model. Different shunt fault types, including line-to-ground, line-to-line, double-line-to-ground, triple-line, and triple-line-to-ground were applied for fault detection and classification framework. Furthermore, the optimum number of hidden neurons in the ELM model was investigated in this study. In terms of the Mean Squared Error (MSE) and correlation coefficient, four ELM variants based on Sine, Sigmoid, Radial Basis, and Triangular Basis transfer functions were assessed for each module. The outcome of these metrics indicates that the ELM with the sigmoid model demonstrated superior performance compared to the other ELM models. Based on statistical metrics MSE, Root Mean Squared Error (RMSE), and Mean Absolute Error (MAE), and also the computational time, the efficiency of ELM-Sigmoid and state-of-the-art methods of Multi-Layer Perceptron Neural Network (MLPNN) and Radial Basis Function Neural Network (RBFNN) were compared and analyzed during training and testing phases. The results obtained revealed that the ELM-Sigmoid model outperforms the other models in the detection and classification of shunt faults with significant accuracy and fast computational speed. ©

关键词： Fault detection

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